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Leetcode #1110: Delete Nodes And Return Forest

In this guide, we solve Leetcode #1110 Delete Nodes And Return Forest in Python and focus on the core idea that makes the solution efficient.

You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.

Leetcode

Problem Statement

Given the root of a binary tree, each node in the tree has a distinct value. After deleting all nodes with a value in to_delete, we are left with a forest (a disjoint union of trees).

Quick Facts

  • Difficulty: Medium
  • Premium: No
  • Tags: Tree, Depth-First Search, Array, Hash Table, Binary Tree

Intuition

Fast membership checks and value lookups are the heart of this problem, which makes a hash map the natural choice.

By storing what we have already seen (or counts/indexes), we can answer the question in one pass without backtracking.

Approach

Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.

This keeps the solution linear while remaining easy to explain in an interview setting.

Steps:

  • Initialize a hash map for seen items or counts.
  • Iterate through the input, querying/updating the map.
  • Return the first valid result or the final computed value.

Example

Input: root = [1,2,3,4,5,6,7], to_delete = [3,5] Output: [[1,2,null,4],[6],[7]]

Python Solution

# Definition for a binary tree node. # class TreeNode: # def __init__(self, val=0, left=None, right=None): # self.val = val # self.left = left # self.right = right class Solution: def delNodes( self, root: Optional[TreeNode], to_delete: List[int] ) -> List[TreeNode]: def dfs(root: Optional[TreeNode]) -> Optional[TreeNode]: if root is None: return None root.left, root.right = dfs(root.left), dfs(root.right) if root.val not in s: return root if root.left: ans.append(root.left) if root.right: ans.append(root.right) return None s = set(to_delete) ans = [] if dfs(root): ans.append(root) return ans

Complexity

The time complexity is O(n)O(n)O(n), and the space complexity is O(n)O(n)O(n). The space complexity is O(n)O(n)O(n).

Edge Cases and Pitfalls

Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.

Summary

This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.


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